Revenue by city with GroupBy

Question

You have an orders DataFrame and the city lead wants total revenue per city, biggest first.

Write a function `revenue_by_city(df)` that returns a **Series** indexed by `city` holding the summed `amount`, sorted from highest to lowest revenue.

Accepted Answer

Step 1: `df.groupby("city")` splits the rows into one group per city. Step 2: Selecting `["amount"]` *before* aggregating keeps the result a Series instead of a DataFrame — cheaper and simpler to sort. Step 3: `.sum()` collapses each group to a single total. Step 4: `.sort_values(ascending=False)` puts the biggest market first. Note `sort_values` sorts by value, `sort_index` would sort alphabetically by city.

Revenue by city with GroupBy

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